Intersegmental dynamics shape joint coordination during catching in typically developing children but not in children with developmental coordination disorder
Bibliographic record
Abstract
Factors shaping joint coordination during multijoint movements were studied using a one-handed ball-catching task. Typically developing (TD) boys between 9 and 12 yr of age, at which catching becomes consistently successful, and boys with developmental coordination disorder (DCD) of the same age participated in the study. The arm was initially stretched down. Catching was performed by flexing the shoulder and elbow and extending the wrist in the parasagittal plane. Catching success rate was substantially lower in children with DCD. Amplitudes and directions of joint motions were similar in both groups. Group differences were found in shoulder and elbow coordination patterns. TD children performed the movement predominantly by actively accelerating into flexion, one joint at a time-first the elbow and then the shoulder-and allowing passive interaction torque (IT) to accelerate the other joint into extension. Children with DCD tended to accelerate both joints into flexion simultaneously, suppressing IT. The results suggest that the TD joint coordination was shaped by the tendency to minimize active control of IT despite the complexity of the emergent joint kinematics. The inefficient control of IT in children with DCD points to deficiency of the internal model of intersegmental dynamics. Together, the findings advocate that joint coordination throughout a multijoint movement is a by-product of the control strategy that benefits from movement dynamics by actively accelerating a single joint and using IT for rotation of the other joint. Reduction of control-dependent noise is discussed as a possible advantage of this control strategy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".